scholarly journals Associations between recently diagnosed conditions and hospitalization due to COVID-19 in patients aged 50 years and older– A SHARE-based analysis

2021 ◽  
Author(s):  
Rubén López-Bueno ◽  
Rodrigo Torres-Castro ◽  
Ai Koyanagi ◽  
Lee Smith ◽  
Pinar Soysal ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Heart Disease ◽  
Lung Disease ◽  
Sample Size ◽  
Chronic Conditions ◽  
Large Sample Size ◽  
Representative Survey ◽  
High Odds ◽  
Large Sample ◽  
The Relationship

Abstract Background Only a few studies have been carried out with a large sample size on the relationship between chronic conditions and hospitalization for COVID-19, and there is no research examining recently diagnosed conditions. Our purpose was to evaluate this association in a large sample including the older population from Europe and Israel. Methods Data from the SHARE COVID-19 Survey, a representative survey of individuals aged 50 or over residing in 27 European countries and Israel, were retrieved. Associations between recently diagnosed chronic conditions (i.e., conditions detected over the last three years) (exposure) and hospitalization due to COVID-19 (outcome) were assessed using multivariable logistic regression. Results 51,514 participants on average 71.0 (SD = 9.2) years old were included. Participants with multimorbidity (i.e., two or more recently diagnosed conditions) had significantly higher odds for COVID-19 hospitalization (AOR = 3.91 [95%CI = 2.14-7.12]). Independent conditions such as lung disease (AOR = 16.94 [95%CI = 9.27-30.95]), heart disease (AOR = 3.29 [95%CI =1.50-7.21]), or cancer (AOR = 3.45 [95%CI = 1.26-9.48]), showed particularly high odds for hospitalization due to COVID-19 disease. Conclusions People with recently diagnosed diseases, and in particular those having lung disease, heart disease, or cancer were significantly more likely to be hospitalized for COVID-19.

scholarly journals Logistic Regression Ensemble for Predicting Customer Defection with Very Large Sample Size

2015 ◽  
Vol 72 ◽  
pp. 86-93 ◽  
Author(s):  
Heri Kuswanto ◽  
Ayu Asfihani ◽  
Yogi Sarumaha ◽  
Hayato Ohwada
Keyword(s):  
Logistic Regression ◽  
Sample Size ◽  
Large Sample Size ◽  
Large Sample ◽  
Customer Defection

scholarly journals Can Peg Strength Be Used as a Predictor for Pod Maturity and Peanut Yield?

2015 ◽  
Vol 42 (2) ◽  
pp. 92-99 ◽  
Author(s):  
R.B. Sorensen ◽  
M.C. Lamb ◽  
C.L. Butts
Keyword(s):  
Sample Size ◽  
Small Difference ◽  
Large Sample Size ◽  
Current Standard ◽  
Color Chart ◽  
Large Sample ◽  
Harvest Dates ◽  
Arachis Hypogaea L ◽  
Peanut Cultivars ◽  
The Relationship

Abstract Mesocarp hull color is the current standard to estimate digging date and peanut (Arachis hypogaea, L.) maturity with acceptable yield and grade. Subjectivity of pod color and pod placement on a color chart may give a false indication of when to dig peanuts. The objective was to determine if peg strength could be used to predict pod maturity, digging date, and resultant peanut yield. Peanut peg strength was collected for two years (2011 and 2012) on three peanut cultivars (Georgia-06G, Georgia-09B, and Tifguard), at multiple plant dates (2012 only) and multiple harvest dates to determine the relationship between peg strength versus pod maturity, peanut loss, and peanut yield. Peg strength was determined using an electronic force gage that would measure peak force. Average peg strength was different for all three cultivars with Georgia-06G having the greatest average peg strength followed by Georgia-09B, and Tifguard. In general, peanut yields were greater at early plant and harvest dates and decreased with time. Conversely, peanut pod loss was lower with early plant and harvest dates but increased with later harvest dates. There was a strong positive linear relationship between peg strength and peanut yield for each cultivar. However, there was a relatively small difference with peg strength values between the maximum and minimum peanut yield. There was no relationship between peg strength and mesocarp color (pod maturity, R2 = 0.007). Small differences in peg strength and the non-relationship between peg strength and pod maturity implies: 1) a large sample size would be needed to predict peanut yield, 2) the large sample size would increase time and manpower to determine average peg strength values, and 3) peg strength was not a valid criteria to determine pod maturity or predict digging date. Overall, peg strength may be useful to describe cultivar characteristics but may not be sufficiently robust to predict pod maturity digging date, or peanut yield.

A Closer Look at Select Cognitive Precursors to Organizational Turnover: What Has Been Missed and Why

1996 ◽  
Vol 78 (3_suppl) ◽  
pp. 1331-1352 ◽  
Author(s):  
J. Bryan Fuller ◽  
Kim Hester ◽  
Pat Dickson ◽  
Barbara J. Allison ◽  
Meg Birdseye
Keyword(s):  
Job Satisfaction ◽  
Sample Size ◽  
Behavioral Intention ◽  
Intention To Leave ◽  
Large Sample Size ◽  
Intention To Stay ◽  
Large Sample ◽  
Integrative Research ◽  
Withdrawal Cognitions ◽  
The Relationship

Two meta-analytic procedures are used to investigate the relationship between job satisfaction and selected withdrawal cognitions. Moderating influences not found in previous integrative research were identified by controlling for the influence of a Large sample-size outlier and a target of behavioral intention, i.e., intention to stay versus, in tendon to leave. Findings for 49 studies indicate previous integrative models of turnover by Hom, Caranikas-Walker, Prussia, and Griffeth, and of Tett and Meyer should be altered to reflect context (civilian versus military) and intention target (staying versus leaving) moderators but not an intention to turnover or a moderator of withdrawal cognition as indicated by Tett and Meyer in 1993. The adequacy of measures of current intention to leave is discussed regarding their consistency with recent intention theory. General implications for meta-analytic research are discussed with regard to accounting for sample-size outliers.

The Birthday-Deathday Effect: Fact or Artifact?

1987 ◽  
Vol 17 (4) ◽  
pp. 321-326 ◽  
Author(s):  
John B. Wood
Keyword(s):  
Heart Disease ◽  
Death Rate ◽  
The Elderly ◽  
Large Sample ◽  
Married People ◽  
The Relationship

The relationship between birthday and deathday has been called an artifact due to the continuous depletion of the population with age. However, while the population decreases with age, the death rate increases. These two influences cancel each other at ages seventy-five to eighty-four. The decreasing population dominates at older ages, but the situation is reversed at younger ages. The results account for no more than one-third of the size of the large-sample effects observed among the elderly. There is still a 33 percent excess of deaths resulting from heart disease among married people ages seventy-five and older in the three-day period centered at the birthday.

Heart Rate Response to Exercise

2018 ◽  
pp. 437-445
Author(s):  
Gregory S. Thomas
Keyword(s):  
Heart Rate ◽  
Physical Fitness ◽  
Sample Size ◽  
Older Persons ◽  
Heart Rate Response ◽  
Large Sample Size ◽  
Maximum Heart Rate ◽  
Large Sample ◽  
Response To Exercise

The chapter Heart Rate Response to Exercise reviews the studies performed to estimate a patient’s maximum predicted heart rate. While the commonly used formula (220 – age), developed in 1971, is easy to remember, it underestimates the actual maximum heart rate in older persons. Studies of large sample size have found the maximum heart rate to be relatively independent of sex and physical fitness but to incrementally decline with age. The decrease with age is less than 1 beat per minute per year, however. A more accurate and recommended formula is [(208) – (0.7)(age)] as developed by Tanaka and colleagues.

Extended criterion for comparison of empirical distributions

1970 ◽  
Vol 7 (01) ◽  
pp. 1-20 ◽  
Author(s):  
Ora Engleberg Percus ◽  
Jerome K. Percus
Keyword(s):  
Sample Size ◽  
Generating Function ◽  
Relative Number ◽  
Function Technique ◽  
Large Sample Size ◽  
Large Sample ◽  
Empirical Distributions ◽  
Asymptotic Problem ◽  
Explicit Expressions

A generating function technique is used to determine the probability that the deviation between two empirical distributions drawn from the same population lies within a given band a specified number of times. We also treat the asymptotic problem of very large sample size, and obtain explicit expressions when the relative number of failures is very small or very large.

scholarly journals A Mass-Ratiometry-Based CD45 Barcoding Method for Mass Cytometry Detection

2019 ◽  
Vol 24 (4) ◽  
pp. 408-419
Author(s):  
Hongu Meng ◽  
Antony Warden ◽  
Lulu Zhang ◽  
Ting Zhang ◽  
Yiyang Li ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Sample Size ◽  
Single Cell ◽  
Large Sample Size ◽  
Single Cell Level ◽  
Mass Cytometry ◽  
Cell Level ◽  
Large Sample ◽  
Antibody Staining ◽  
Instrument Sensitivity

Mass cytometry (CyTOF) is a critical cell profiling tool in acquiring multiparameter proteome data at the single-cell level. A major challenge in CyTOF analysis is sample-to-sample variance arising from the pipetting process, staining variation, and instrument sensitivity. To reduce such variations, cell barcoding strategies that enable the combination of individual samples prior to antibody staining and data acquisition on CyTOF are often utilized. The most prevalent barcoding strategy is based on a binary scheme that cross-examines the existence or nonexistence of certain mass signals; however, it is limited by low barcoding efficiency and high cost, especially for large sample size. Herein, we present a novel barcoding method for CyTOF application based on mass ratiometry. Different mass tags with specific fixed ratios are used to label CD45 antibody to achieve sample barcoding. The presented method exponentially increases the number of possible barcoded samples with the same amount of mass tags compared with conventional methods. It also reduces the overall time for the labeling process to 40 min and avoids the need for expensive commercial barcoding buffer reagents. Moreover, unlike the conventional barcoding process, this strategy does not pre-permeabilize cells before the barcoding procedure, which offers additional benefits in preserving surface biomarker signals.

MoFe‐Codoped Ni 3 S 2 /Ni(OH) 2 Nanosheets with Large Sample Size toward High‐Performance Oxygen Evolution

2019 ◽  
Vol 7 (9) ◽  
pp. 1801053
Author(s):  
Liu Xie ◽  
Rui Tong ◽  
Wen Zhang ◽  
Dejian Wang ◽  
Tao Liu ◽  
...  
Keyword(s):  
Sample Size ◽  
Oxygen Evolution ◽  
High Performance ◽  
Large Sample Size ◽  
Large Sample
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